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GPT3Discord
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Merge branch 'main' of https://github.com/Kav-K/GPT3Discord

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Kaveen Kumarasinghe 2 years ago
parent 24cd5011c4 0ed400a505
commit 4f8d4afd6b
2 changed files with 86 additions and 63 deletions
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128
cogs/gpt_3_commands_and_converser.py
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@ -29,14 +29,14 @@ original_message = {}
class GPT3ComCon(commands.Cog, name="GPT3ComCon"): class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
def __init__( def __init__(
self, self,
bot, bot,
usage_service, usage_service,
model, model,
message_queue, message_queue,
deletion_queue, deletion_queue,
DEBUG_GUILD, DEBUG_GUILD,
DEBUG_CHANNEL, DEBUG_CHANNEL,
): ):
self.debug_channel = None self.debug_channel = None
self.bot = bot self.bot = bot
@ -134,13 +134,13 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
def check_conversing(self, message): def check_conversing(self, message):
cond1 = ( cond1 = (
message.author.id in self.conversating_users message.author.id in self.conversating_users
and message.channel.name in ["gpt3", "general-bot", "bot"] and message.channel.name in ["gpt3", "general-bot", "bot"]
) )
cond2 = ( cond2 = (
message.author.id in self.conversating_users message.author.id in self.conversating_users
and message.author.id in self.conversation_threads and message.author.id in self.conversation_threads
and message.channel.id == self.conversation_threads[message.author.id] and message.channel.id == self.conversation_threads[message.author.id]
) )
# If the trimmed message starts with a Tilde, then we want to not contribute this to the conversation # If the trimmed message starts with a Tilde, then we want to not contribute this to the conversation
@ -286,7 +286,7 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
async def paginate_and_send(self, response_text, message): async def paginate_and_send(self, response_text, message):
response_text = [ response_text = [
response_text[i: i + self.TEXT_CUTOFF] response_text[i : i + self.TEXT_CUTOFF]
for i in range(0, len(response_text), self.TEXT_CUTOFF) for i in range(0, len(response_text), self.TEXT_CUTOFF)
] ]
# Send each chunk as a message # Send each chunk as a message
@ -303,7 +303,7 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
async def queue_debug_chunks(self, debug_message, message, debug_channel): async def queue_debug_chunks(self, debug_message, message, debug_channel):
debug_message_chunks = [ debug_message_chunks = [
debug_message[i: i + self.TEXT_CUTOFF] debug_message[i : i + self.TEXT_CUTOFF]
for i in range(0, len(debug_message), self.TEXT_CUTOFF) for i in range(0, len(debug_message), self.TEXT_CUTOFF)
] ]
@ -346,8 +346,8 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
if message.author.id in self.conversating_users: if message.author.id in self.conversating_users:
# If the user has reached the max conversation length, end the conversation # If the user has reached the max conversation length, end the conversation
if ( if (
self.conversating_users[message.author.id].count self.conversating_users[message.author.id].count
>= self.model.max_conversation_length >= self.model.max_conversation_length
): ):
await message.reply( await message.reply(
"You have reached the maximum conversation length. You have ended the conversation with GPT3, and it has ended." "You have reached the maximum conversation length. You have ended the conversation with GPT3, and it has ended."
@ -360,14 +360,19 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
new_conversation_history = [] new_conversation_history = []
new_conversation_history.append(self.CONVERSATION_STARTER_TEXT) new_conversation_history.append(self.CONVERSATION_STARTER_TEXT)
new_conversation_history.append("\nThis conversation has some context from earlier, which has been summarized as follows: ") new_conversation_history.append(
"\nThis conversation has some context from earlier, which has been summarized as follows: "
)
new_conversation_history.append(summarized_text) new_conversation_history.append(summarized_text)
new_conversation_history.append("\nContinue the conversation, paying very close attention to things Human told you, such as their name, and personal details.\n") new_conversation_history.append(
"\nContinue the conversation, paying very close attention to things Human told you, such as their name, and personal details.\n"
)
# Get the last entry from the user's conversation history # Get the last entry from the user's conversation history
new_conversation_history.append(self.conversating_users[message.author.id].history[-1]+"\n") new_conversation_history.append(
self.conversating_users[message.author.id].history[-1] + "\n"
)
self.conversating_users[message.author.id].history = new_conversation_history self.conversating_users[message.author.id].history = new_conversation_history
async def encapsulated_send(self, message, prompt, response_message=None): async def encapsulated_send(self, message, prompt, response_message=None):
# Append a newline, and GPTie: to the prompt # Append a newline, and GPTie: to the prompt
@ -381,33 +386,42 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
tokens = self.usage_service.count_tokens(new_prompt) tokens = self.usage_service.count_tokens(new_prompt)
if tokens > self.model.summarize_threshold: # 250 is a buffer if tokens > self.model.summarize_threshold: # 250 is a buffer
if self.model.summarize_conversations: if self.model.summarize_conversations:
await message.reply( await message.reply(
"I'm currently summarizing our current conversation so we can keep chatting, " "I'm currently summarizing our current conversation so we can keep chatting, "
"give me one moment!") "give me one moment!"
)
self.summarize_conversation(message, new_prompt) self.summarize_conversation(message, new_prompt)
# Check again if the prompt is about to go past the token limit # Check again if the prompt is about to go past the token limit
new_prompt = "".join(self.conversating_users[message.author.id].history) + "\nGPTie: " new_prompt = (
"".join(self.conversating_users[message.author.id].history)
+ "\nGPTie: "
)
tokens = self.usage_service.count_tokens(new_prompt) tokens = self.usage_service.count_tokens(new_prompt)
if tokens > self.model.summarize_threshold - 150: # 150 is a buffer for the second stage if (
await message.reply("I tried to summarize our current conversation so we could keep chatting, " tokens > self.model.summarize_threshold - 150
"but it still went over the token " ): # 150 is a buffer for the second stage
"limit. Please try again later.") await message.reply(
"I tried to summarize our current conversation so we could keep chatting, "
"but it still went over the token "
"limit. Please try again later."
)
await self.end_conversation(message)
return
else:
await message.reply("The conversation context limit has been reached.")
await self.end_conversation(message) await self.end_conversation(message)
return return
else:
await message.reply(
"The conversation context limit has been reached."
)
await self.end_conversation(message)
return
response = self.model.send_request(new_prompt, message) response = self.model.send_request(new_prompt, message)
response_text = response["choices"][0]["text"] response_text = response["choices"][0]["text"]
if re.search(r"<@!?\d+>|<@&\d+>|<#\d+>", response_text): if re.search(r"<@!?\d+>|<@&\d+>|<#\d+>", response_text):
@ -444,8 +458,9 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
original_message[message.author.id] = message.id original_message[message.author.id] = message.id
else: else:
# We have response_text available, this is the original message that we want to edit # We have response_text available, this is the original message that we want to edit
await response_message.edit(content=response_text.replace("<|endofstatement|>", "")) await response_message.edit(
content=response_text.replace("<|endofstatement|>", "")
)
# After each response, check if the user has reached the conversation limit in terms of messages or time. # After each response, check if the user has reached the conversation limit in terms of messages or time.
await self.check_conversation_limit(message) await self.check_conversation_limit(message)
@ -484,17 +499,18 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
if after.author.id in self.conversating_users: if after.author.id in self.conversating_users:
# Remove the last two elements from the history array and add the new Human: prompt # Remove the last two elements from the history array and add the new Human: prompt
self.conversating_users[after.author.id].history = self.conversating_users[after.author.id].history[ self.conversating_users[
:-2] after.author.id
].history = self.conversating_users[after.author.id].history[:-2]
self.conversating_users[after.author.id].history.append( self.conversating_users[after.author.id].history.append(
f"\nHuman: {after.content}<|endofstatement|>\n") f"\nHuman: {after.content}<|endofstatement|>\n"
edited_content = "".join(self.conversating_users[after.author.id].history) )
edited_content = "".join(
self.conversating_users[after.author.id].history
)
self.conversating_users[after.author.id].count += 1 self.conversating_users[after.author.id].count += 1
await self.encapsulated_send( await self.encapsulated_send(message, edited_content, response_message)
message,
edited_content, response_message
)
redo_users[after.author.id].prompt = after.content redo_users[after.author.id].prompt = after.content
@ -536,7 +552,7 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
# A global GLOBAL_COOLDOWN_TIME timer for all users # A global GLOBAL_COOLDOWN_TIME timer for all users
if (message.author.id in self.last_used) and ( if (message.author.id in self.last_used) and (
time.time() - self.last_used[message.author.id] < self.GLOBAL_COOLDOWN_TIME time.time() - self.last_used[message.author.id] < self.GLOBAL_COOLDOWN_TIME
): ):
await message.reply( await message.reply(
"You must wait " "You must wait "
@ -581,9 +597,9 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
# If the user is not already conversating, start a conversation with GPT3 # If the user is not already conversating, start a conversation with GPT3
self.conversating_users[message.author.id] = User(message.author.id) self.conversating_users[message.author.id] = User(message.author.id)
# Append the starter text for gpt3 to the user's history so it gets concatenated with the prompt later # Append the starter text for gpt3 to the user's history so it gets concatenated with the prompt later
self.conversating_users[ self.conversating_users[message.author.id].history.append(
message.author.id self.CONVERSATION_STARTER_TEXT
].history.append(self.CONVERSATION_STARTER_TEXT) )
# Create a new discord thread, and then send the conversation starting message inside of that thread # Create a new discord thread, and then send the conversation starting message inside of that thread
if not ("nothread" in prompt): if not ("nothread" in prompt):
@ -625,16 +641,16 @@ class GPT3ComCon(commands.Cog, name="GPT3ComCon"):
# we can append their history to the prompt. # we can append their history to the prompt.
if message.author.id in self.conversating_users: if message.author.id in self.conversating_users:
self.conversating_users[message.author.id].history.append( self.conversating_users[message.author.id].history.append(
"\nHuman: " "\nHuman: " + prompt + "<|endofstatement|>\n"
+ prompt
+ "<|endofstatement|>\n"
) )
# increment the conversation counter for the user # increment the conversation counter for the user
self.conversating_users[message.author.id].count += 1 self.conversating_users[message.author.id].count += 1
# Send the request to the model # Send the request to the model
await self.encapsulated_send(message, "".join(self.conversating_users[message.author.id].history)) await self.encapsulated_send(
message, "".join(self.conversating_users[message.author.id].history)
)
class RedoView(discord.ui.View): class RedoView(discord.ui.View):

21
models/openai_model.py
Unescape View File

@ -82,7 +82,9 @@ class Model:
def summarize_threshold(self, value): def summarize_threshold(self, value):
value = int(value) value = int(value)
if value < 800 or value > 4000: if value < 800 or value > 4000:
raise ValueError("Summarize threshold cannot be greater than 4000 or less than 800!") raise ValueError(
"Summarize threshold cannot be greater than 4000 or less than 800!"
)
self._summarize_threshold = value self._summarize_threshold = value
@property @property
@ -292,9 +294,11 @@ class Model:
Sends a summary request to the OpenAI API Sends a summary request to the OpenAI API
""" """
summary_request_text = [] summary_request_text = []
summary_request_text.append("The following is a conversation instruction set and a conversation" summary_request_text.append(
" between two people named Human, and GPTie. Do not summarize the instructions for GPTie, only the conversation. Summarize the conversation in a detailed fashion. If Human mentioned their name, be sure to mention it in the summary. Pay close attention to things the Human has told you, such as personal details.") "The following is a conversation instruction set and a conversation"
summary_request_text.append(prompt+"\nDetailed summary of conversation: \n") " between two people named Human, and GPTie. Do not summarize the instructions for GPTie, only the conversation. Summarize the conversation in a detailed fashion. If Human mentioned their name, be sure to mention it in the summary. Pay close attention to things the Human has told you, such as personal details."
)
summary_request_text.append(prompt + "\nDetailed summary of conversation: \n")
summary_request_text = "".join(summary_request_text) summary_request_text = "".join(summary_request_text)
@ -327,7 +331,10 @@ class Model:
frequency_penalty_override=None, frequency_penalty_override=None,
presence_penalty_override=None, presence_penalty_override=None,
max_tokens_override=None, max_tokens_override=None,
) -> (dict, bool): # The response, and a boolean indicating whether or not the context limit was reached. ) -> (
dict,
bool,
): # The response, and a boolean indicating whether or not the context limit was reached.
# Validate that all the parameters are in a good state before we send the request # Validate that all the parameters are in a good state before we send the request
if len(prompt) < self.prompt_min_length: if len(prompt) < self.prompt_min_length:
@ -361,7 +368,7 @@ class Model:
else frequency_penalty_override, else frequency_penalty_override,
best_of=self.best_of if not best_of_override else best_of_override, best_of=self.best_of if not best_of_override else best_of_override,
) )
#print(response.__dict__) # print(response.__dict__)
# Parse the total tokens used for this request and response pair from the response # Parse the total tokens used for this request and response pair from the response
tokens_used = int(response["usage"]["total_tokens"]) tokens_used = int(response["usage"]["total_tokens"])
@ -378,7 +385,7 @@ class Model:
+ str(words) + str(words)
) )
#print("The prompt about to be sent is " + prompt) # print("The prompt about to be sent is " + prompt)
self.usage_service.update_usage_image(self.image_size) self.usage_service.update_usage_image(self.image_size)
if not vary: if not vary:

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